Journal of Preventive Medicine and Public Health最新文献

Objectives: Young children's feeding characteristics can play an important role in eating habits and health during later childhood. This study was conducted to examine the associations of feeding characteristics with dietary patterns and obesity in children.

Methods: This study utilized data from the Korea National Health and Nutrition Examination Survey conducted between 2013 and 2017. In total, 802 toddlers were included, with information on their demographic characteristics, feeding practices and duration, and 24-hour recall obtained from their parents. Feeding characteristics were categorized into feeding type, duration of total breastfeeding, duration of total formula feeding, duration of exclusive breastfeeding, and age when starting formula feeding. Dietary patterns were identified based on factor loadings for the food groups for 3 major factors, with "vegetables & traditional," "fish & carbohydrates," and "sweet & fat" patterns. Overweight/obesity was defined as ≥85th percentile in body mass index based on the 2017 Korean National Growth charts for children and adolescents. Multiple regression analysis was conducted to examine associations between feeding characteristics and dietary patterns. The association between dietary patterns and obesity was analyzed using multivariable logistic regression analysis.

Results: The early introduction of formula feeding was inversely associated with the "vegetables & traditional" pattern (β=-0.18; 95% confidence interval [CI], -0.34 to -0.02). A higher "vegetables & traditional" intake was associated with a lower risk of obesity (odds ratio, 0.48; 95% CI, 0.24 to 0.95).

Conclusions: Feeding characteristics are associated with dietary patterns in later childhood, and dietary patterns were shown to have a potential protective association against obesity.

Objectives: We investigated trends in the incidence rate of macrosomia and its association with parental nationalities using Vital Statistics data in Japan.

Methods: We used singleton birth data every 5 years from 1995 to 2020. The incidence rate of macrosomia was calculated according to specific attributes (maternal age, infant's sex, parental nationalities, parity, and household occupation) over time (years). In addition, a log-binomial model was used to investigate the relationship between the incidence of macrosomia and the attributes. This study compared Korea, China, the Philippines, Brazil, and other countries with Japan in terms of parental nationalities. "Other countries" indicates countries except for Japan, Korea, China, the Philippines, and Brazil.

Results: The study included 6 180 787 births. The rate of macrosomia in Japan decreased from 1.43% in 1995 to 0.88% in 2020, and the decrease was observed across all parental nationalities. The rates for Japanese parents were the lowest values among parental nationalities during the timespan investigated. Multivariate regression analysis showed that mothers from Korea, China, the Philippines, Brazil, and other countries had a significantly higher risk of macrosomia than those from Japan (risk ratio, 1.91, 2.82, 1.59, 1.74, and 1.64, respectively). Furthermore, fathers from China, the Philippines, Brazil, and other countries had a significantly higher risk of macrosomia than those from Japan (risk ratio, 1.66, 1.38, 1.88, and 3.02, respectively).

Conclusions: The rate of macrosomia decreased from 1995 to 2020 in Japan for parents of all nationalities, and the risk of macrosomia incidence was associated with parental nationality.

Objectives: We reviewed the operational definitions of colorectal cancer (CRC) from studies using the Korean National Health Insurance Service (NHIS) and compared CRC incidence derived from the commonly used operational definitions in the literature with the statistics reported by the Korea Central Cancer Registry (KCCR).

Methods: We searched the MEDLINE and KoreaMed databases to identify studies containing operational definitions of CRC, published until January 15, 2021. All pertinent data concerning the study period, the utilized database, and the outcome variable were extracted. Within the NHIS-National Sample Cohort, age-standardized incidence rates (ASRs) of CRC were calculated for each operational definition found in the literature between 2005 and 2019. These rates were then compared with ASRs from the KCCR.

Results: From the 62 eligible studies, 9 operational definitions for CRC were identified. The most commonly used operational definition was "C18-C20" (n=20), followed by "C18-C20 with claim code for treatment" (n=3) and "C18-C20 with V193 (code for registered cancer patients' payment deduction)" (n=3). The ASRs reported using these operational definitions were lower than the ASRs from KCCR, except for "C18-C20 used as the main diagnosis." The smallest difference in ASRs was observed for "C18-C20," followed by "C18- C20 with V193," and "C18-C20 with claim code for hospitalization or code for treatment."

Conclusions: In defining CRC patients utilizing the NHIS database, the ASR derived through the operational definition of "C18-C20 as the main diagnosis" was comparable to the ASR from the KCCR. Depending on the study hypothesis, operational definitions using treatment codes may be utilized.

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic.

Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher.

Results: Participants' mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95).

Conclusions: The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.

Traditional mediation analysis, which relies on linear regression models, has faced criticism due to its limited suitability for cases involving different types of variables and complex covariates, such as interactions. This can result in unclear definitions of direct and indirect effects. As an alternative, causal mediation analysis using the counterfactual framework has been introduced to provide clearer definitions of direct and indirect effects while allowing for more flexible modeling methods. However, the conceptual understanding of this approach based on the counterfactual framework remains challenging for applied researchers. To address this issue, the present article was written to highlight and illustrate the definitions of causal estimands, including controlled direct effect, natural direct effect, and natural indirect effect, based on the key concept of nested counterfactuals. Furthermore, we recommend using 2 R packages, 'medflex' and 'mediation', to perform causal mediation analysis and provide public health examples. The article also offers caveats and guidelines for accurate interpretation of the results.

Objectives: Considering the importance of social determinants of health (SDHs) in promoting the health of residents of informal settlements and their diversity, abundance, and breadth, this study aimed to identify, measure, and rank SDHs for health promotion interventions targeting informal settlement residents in a metropolitan area in Iran.

Methods: Using a hybrid method, this study was conducted in 3 phases from 2019 to 2020. SDHs were identified by reviewing studies and using the Delphi method. To examine the SDHs among informal settlement residents, a cross-sectional analysis was conducted using researcher-made questionnaires. Multilayer perceptron analysis using an artificial neural network was used to rank the SDHs by priority.

Results: Of the 96 determinants identified in the first phase of the study, 43 were examined, and 15 were identified as high-priority SDHs for use in health-promotion interventions for informal settlement residents in the study area. They included individual health literacy, nutrition, occupational factors, housing-related factors, and access to public resources.

Conclusions: Since identifying and addressing SDHs could improve health justice and mitigate the poor health status of settlement residents, ranking these determinants by priority using artificial intelligence will enable policymakers to improve the health of settlement residents through interventions targeting the most important SDHs.